Improvements in positioning systems are making autonomous machines, such as autonomous earthmoving machines a reality.
In order to achieve autonomy, a machine must at all times be able to determine it position relative to its environment. One system commonly used to achieve this goal is the Global Positioning System or GPS. The GPS consists of a plurality of satellites which transmit electromagnetic signals. A GPS receiver located within the range of the satellites receives signals from the satellites and determines the position of the receiver using triangulation methods.
However, there are numerous occasions where GPS is not accurate or usable. For example, the signals from the GPS satellites may be blocked by obstructions or the accuracy of the GPS receiver determined position may be decreased by other causes.
It is possible to use a GPS receiver alone for positioning. However, when high accuracy is required, integrated positioning systems are preferred. An integrated positioning system uses measurements from several different types of sensors to achieve highly accurate positioning information.
Many examples of integrated positioning systems are known. Such integrated systems use GPS navigation signals as well as measurements from inertial and other machine motion type sensors to produce more accurate position estimates. However, these systems are generally of custom design and are therefore expensive and burdensome to implement.
One such system is disclosed in U.S. Pat. No. 5,390,125, granted Feb. 14, 1995, "Machine Position Determination System and Method". The system disclosed in the '125 patent determines machine position using a machine positioning system (VPS). The VPS determines an accurate estimate of machine position by performing a weighted average of a first position estimate and a second position estimate. The first position estimate is received from a global positioning system (GPS) receiver. The second position estimate is received from an inertial navigation unit (INU). The first and second position estimates are weighted as a function of their predicted accuracy to produce a more accurate third position estimate. Such a system as that disclosed in the '125 patent tends to be very expensive.
Other systems combine signals from the GPS receiver and the INU using a Kalman filter. These systems are generally of two types: a loosely coupled system or a tightly coupled system.
The loosely coupled system is the simplest. These systems assume that the GPS data is accurate. Generally, they have a minimum number of states or inputs into the Kalman filter, e.g., GPS North, GPS East, GPS velocity north, GPS velocity east, INU North, INU East, INU velocity north, INU velocity east, and INU heading rate. However, a loosely coupled system is less accurate than a tightly coupled system.
The tightly coupled system does not assume that position data, as determined by the GPS is accurate. Rather, it uses the raw data from the GPS receiver and combines it with data from the INU. Thus, the number of required Kalman filter states increases dramatically. This results in greater complexity and added cost.
The present invention is directed at one or more of the problems as set forth above.